1. Technical Field of the Invention
The present invention relates to a fingerprint/palmprint image processor, processing method, and processing program to be used for fingerprint identification, fingerprint classification, and palmprint identification.
2. Description of the Related Art
Conventionally, as a method for automatically extracting ridge information including ridge directions and ridge pitches from a fingerprint image, for example, a ridge direction pattern smoothing method and device are disclosed in Japanese Patent Publication No. 2765335, and a fingerprint pattern classification by means of a relaxation method was proposed by Kawagoe et al. in the 22nd Information Processing Society of Japan (first term of 1981). The ridge direction pattern smoothing method and device are based on the energy minimizing principle, wherein evaluation functions are set for directions extracted from each two-dimensional local region set on an image by taking the degree of reliability as a measure, and the evaluation functions are minimized for smoothing. On the other hand, in fingerprint pattern classification by means of the relaxation method, information on directions extracted from each two-dimensional local region set on an image is smoothed by means of the relaxation method.
However, in the method disclosed in Japanese Patent Publication No. 2765335, when smoothing an image including creases, surrounding regions may also be smoothed in accordance with creases, resulting in emphasized creases. In the art described in fingerprint pattern classification by means of the relaxation method, the relaxation method is used as a method for smoothing information on directions extracted from each local region, however, in this method, smoothing may be applied to many creases that exist across a wide range of the fingerprint in parallel to each other at similar pitches in accordance with the creases, so that the creases may be emphasized.
Therefore, the inventor of the present invention proposed a fingerprint/palmprint image processor which can extract a ridge image from a fingerprint/palmprint image without influences from creases in Japanese Unexamined Patent Publication No. Hei-9-167230. In the processor disclosed in this publication, an inputted fingerprint/palmprint image is divided into a plurality of blocks, and a plurality of ridge candidates are detected from each block, and among the detected ridge candidates, ridge candidates that can be securely judged as ridges and the blocks including the ridge candidates are determined, and candidates in other blocks matching with the determined ridge candidates are selected. The ridge patterns are spatially continued with each other and the crease patterns are spatially continued with each other, however, generally, creases and ridges are not continued with each other, so that candidates that can be securely judged as ridges are detected, and candidates matching with the detected candidates are selected among other local candidates, whereby it becomes possible to accurately detect ridges even in regions with creases.
FIG. 1 shows the relationship between the parts of the abovementioned fingerprint/palmprint image processor. FIG. 1 corresponds to FIG. 9 of Japanese Unexamined Patent Publication No. Hei-9-167230. However, for easy explanation, FIG. 1 is a simplified drawing of FIG. 9 of the same publication. In FIG. 1, reference numeral 11 denotes an image input part, reference numeral 12 denotes a local information extracting part, reference numeral 13 denotes a highly reliable region determining part, reference numeral 14 denotes an adjacent region group detecting part, reference numeral 15 denotes a ridge candidate selecting part, and reference numeral 16 denotes an image generating part. Herein, the highly reliable region determining part 13 corresponds to the first ridge candidate image selecting part 12, continuity evaluating part 13, clustering part 14, and cluster evaluating part 15 of the same publication. The adjacent region group detecting part 14 and ridge candidate selecting part 15 correspond to the optimum ridge candidate image selecting part 17.
FIG. 2 is a flowchart showing the operation of the processor of FIG. 1. In FIG. 2, the image input part 11 reads-in a fingerprint/palmprint as an image, and supplies it to the local information extracting part 12 in the form of a digital image (S701). The local information extracting part 12 divides the inputted original image into two-dimensional local regions (S702), and extracts a plurality of images that are candidates rendering ridges existing in each local region (hereinafter, referred to as ridge candidate images) (S703). Numeral numbers are attached to each extracted ridge candidate image. The extracted ridge candidate images are supplied to the highly reliable region determining part 13, ridge candidate selecting part 14, and image generating part 16, respectively. In the highly reliable region determining part 13, ridge candidates that are highly likely to be defined as ridges among a plurality of ridge candidate images and local regions including the ridges (highly reliable regions) are determined (S704), and the ridge candidates and local regions are supplied to the adjacent region group detecting part 14, ridge candidate selecting part 15, and image generating part 16, respectively.
The adjacent region group detecting part 14 finds all local regions (adjacent regions) adjacent to the highly reliable regions (S705). For example, as shown in FIG. 3A, when the highly reliable regions (shown by dark hatching) are found, the regions (shown by light hatching) adjacent to the highly reliable regions are detected as adjacent regions. Next, it is judged whether or not the number of adjacent regions is one or more (S706). For example, in the example of FIG. 3A, since the number of adjacent regions is more than one, the process progresses to S707, and ridge images are selected among ridge candidate images for each of all the adjacent regions detected by the ridge candidate selecting part 15, and the image generating part 16 is notified of the selected candidate numbers.
For example, when candidate selection processing is carried out for the adjacent region A of FIG. 3A, a candidate having high continuity is selected among ridge candidate images 1 through 6, and in this case, the candidate image 2 is selected. Next, the process returns to S705, and with respect to a highly reliable region or a local region selection for which the process has ended, all adjacent regions that are neither highly reliable regions nor regions selection for which the process has ended are detected. That is, in the case of FIG. 3A, all regions adjacent to lower sides to the previously found adjacent regions are found. Next, it is judged whether or not the number of adjacent regions is one or more in S706, and when the number is one or more, ridge images are selected from the ridge candidate images of all adjacent regions in S707. Then, processing from S705 to S707 is repeated. When “NO” is judged in S706, processing has ended for all local regions, so that the image generating part 16 creates a whole ridge image by using the selected candidate images as shown in FIG. 3B (S708).
In the fingerprint/palmprint image processor disclosed in Japanese Unexamined Patent Publication No. Hei-9-167230 of 1997 mentioned above, it is possible to extract ridges without influence from creases, however, since ridge images are determined for each local region by taking the continuity with adjacent regions as important, at a portion including ridges with great curvatures such as the core shown in FIG. 4A or the delta shown in FIG. 4B, image candidates including creases with good continuity may be selected rather than images including ridges even when the ridges are clear, resulting in a failure of ridge extraction.